Endorsement of the 66/68 Joint Count for the Measurement of Musculoskeletal Disease Activity: OMERACT 2018 Psoriatic Arthritis Workshop Report
Bibliographic record
Abstract
OBJECTIVE: The Psoriatic Arthritis (PsA) Core Domain Set for randomized controlled trials and longitudinal observational studies has recently been updated. The joint counts are central to the measurement of the peripheral arthritis component of the musculoskeletal (MSK) disease activity domain. We report the Outcome Measures in Rheumatology (OMERACT) 2018 meeting's approaches to seek endorsement of the 66/68 swollen and tender joint count (SJC66/TJC68) for inclusion in the PsA Core Outcome Measurement Set (COS). METHODS: Using the OMERACT Filter 2.1 Instrument Selection Process, the SJC66/TJC68 was assessed for (1) domain match, (2) feasibility, (3) numerical sense (construct validity), and (4) discrimination (test retest reliability, longitudinal construct validity, sensitivity in clinical trials, and thresholds of meaning). A protocol was designed to assess the measurement properties of the SJC66/TJC68 joint count. The results were summarized in a Summary of Measurement Properties table developed by OMERACT. OMERACT members discussed and voted on whether the strength of the evidence supported that the SJC66/TJC68 had passed the OMERACT Filter as an outcome measurement instrument for the PsA COS. RESULTS: OMERACT delegates endorsed the use of the SJC66/TJC68 for the measurement of the peripheral arthritis component of the MSK disease activity domain. Among patient research partners, 100% voted for a "green" endorsement, whereas among the group of other stakeholders, 88% voted for a "green" endorsement. CONCLUSION: The SJC66/TJC68 is the first fully endorsed outcome measurement instrument using the OMERACT Filter 2.1 and the first instrument fully endorsed within the PsA COS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.194 | 0.222 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".